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Question:In Exercises 15–18, find a basis for the space spanned by the given vectors,\({{\bf{v}}_{\bf{1}}}, \ldots ,{{\bf{v}}_{\bf{5}}}\).

16. \(\left[ {\begin{array}{*{20}{c}}1\\{\bf{0}}\\{\bf{0}}\\{\bf{1}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - {\bf{2}}}\\{\bf{1}}\\{ - {\bf{1}}}\\{\bf{1}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{6}}\\{ - {\bf{1}}}\\{\bf{2}}\\{ - {\bf{1}}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{5}}\\{ - {\bf{3}}}\\{\bf{3}}\\{ - {\bf{4}}}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{\bf{0}}\\{\bf{3}}\\{ - {\bf{1}}}\\{\bf{1}}\end{array}} \right]\)

Short Answer

Expert verified

The basis for the space spanned by the vectors is \(\left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\0\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 2}\\1\\{ - 1}\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}6\\{ - 1}\\2\\{ - 1}\end{array}} \right]} \right\}\).

Step by step solution

01

State the basis for Col A

The set of alllinear combinations of the columns of matrix A is Col A.It is called thecolumn space of A.Pivot columns are thebasisfor Col A.

02

Obtain the row-reduced echelon form

Consider the vectors\(\left[ {\begin{array}{*{20}{c}}1\\0\\0\\1\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - 2}\\1\\{ - 1}\\1\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}6\\{ - 1}\\2\\{ - 1}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}5\\{ - 3}\\3\\{ - 4}\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}0\\3\\{ - 1}\\1\end{array}} \right]\).

Five vectors span the column spaceof a matrix. So, construct matrix A using the given vectors as shown below:

\(A = \left[ {\begin{array}{*{20}{c}}1&{ - 2}&6&5&0\\0&1&{ - 1}&{ - 3}&3\\0&{ - 1}&2&3&{ - 1}\\1&1&{ - 1}&{ - 4}&1\end{array}} \right]\)

Obtain theechelon formof matrix A as shown below:

Add\( - 1\)times row 1 to row 4 to get row 4.

\(A = \left[ {\begin{array}{*{20}{c}}1&{ - 2}&6&5&0\\0&1&{ - 1}&{ - 3}&3\\0&{ - 1}&2&3&{ - 1}\\0&3&{ - 7}&{ - 9}&1\end{array}} \right]\)

Add row 2 to row 3 to get row 3.

\(A = \left[ {\begin{array}{*{20}{c}}1&{ - 2}&6&5&0\\0&1&{ - 1}&{ - 3}&3\\0&0&1&0&2\\0&3&{ - 7}&{ - 9}&1\end{array}} \right]\)

Add\( - 3\)times row 2 to row 4 to get row 4.

\(A = \left[ {\begin{array}{*{20}{c}}1&{ - 2}&6&5&0\\0&1&{ - 1}&{ - 3}&3\\0&0&1&0&2\\0&0&{ - 4}&0&{ - 8}\end{array}} \right]\)

Add 4 times row 3 to row 4 to get row 4.

\(A = \left[ {\begin{array}{*{20}{c}}1&{ - 2}&6&5&0\\0&1&{ - 1}&{ - 3}&3\\0&0&1&0&2\\0&0&0&0&0\end{array}} \right]\)

03

Write the basis for Col A

To identify the pivot and the pivot position, observe the leftmost column (nonzero column) of the matrix, that is, the pivot column. At the top of this column, 1 is the pivot.

A = \(\left[ {\begin{array}{*{20}{c}} {\boxed1}&{ - 2}&6&5&0 \\ 0&{\boxed1}&{ - 1}&{ - 3}&3 \\ 0&0&{\boxed1}&0&2 \\ 0&0&0&0&0 \end{array}} \right]\)

The first, second, and third columns have pivot elements.

The corresponding columns of matrix A are shown below:

\(\left[ {\begin{array}{*{20}{c}}1\\0\\0\\1\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - 2}\\1\\{ - 1}\\1\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}6\\{ - 1}\\2\\{ - 1}\end{array}} \right]\)

The column space is shown below:

\({\rm{Col }}A = \left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\0\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 2}\\1\\{ - 1}\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}6\\{ - 1}\\2\\{ - 1}\end{array}} \right]} \right\}\)

Thus, the basis for Col Ais \(\left\{ {\left[ {\begin{array}{*{20}{c}}1\\0\\0\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}{ - 2}\\1\\{ - 1}\\1\end{array}} \right],\left[ {\begin{array}{*{20}{c}}6\\{ - 1}\\2\\{ - 1}\end{array}} \right]} \right\}\).

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Most popular questions from this chapter

In Exercise 17, Ais an \(m \times n\] matrix. Mark each statement True or False. Justify each answer.

17. a. The row space of A is the same as the column space of \({A^T}\].

b. If B is any echelon form of A, and if B has three nonzero rows, then the first three rows of A form a basis for Row A.

c. The dimensions of the row space and the column space of A are the same, even if Ais not square.

d. The sum of the dimensions of the row space and the null space of A equals the number of rows in A.

e. On a computer, row operations can change the apparent rank of a matrix.

If A is a \({\bf{4}} \times {\bf{3}}\) matrix, what is the largest possible dimension of the row space of A? If Ais a \({\bf{3}} \times {\bf{4}}\) matrix, what is the largest possible dimension of the row space of A? Explain.

In statistical theory, a common requirement is that a matrix be of full rank. That is, the rank should be as large as possible. Explain why an m n matrix with more rows than columns has full rank if and only if its columns are linearly independent.

Consider the polynomials \({p_{\bf{1}}}\left( t \right) = {\bf{1}} + {t^{\bf{2}}},{p_{\bf{2}}}\left( t \right) = {\bf{1}} - {t^{\bf{2}}}\). Is \(\left\{ {{p_{\bf{1}}},{p_{\bf{2}}}} \right\}\) a linearly independent set in \({{\bf{P}}_{\bf{3}}}\)? Why or why not?

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

  1. Show that if \(B\) is \(n \times p\), then rank\(AB \le {\mathop{\rm rank}\nolimits} A\). (Hint: Explain why every vector in the column space of \(AB\) is in the column space of \(A\).
  2. Show that if \(B\) is \(n \times p\), then rank\(AB \le {\mathop{\rm rank}\nolimits} B\). (Hint: Use part (a) to study rank\({\left( {AB} \right)^T}\).)
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